Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 0 |
Since 2006 (last 20 years) | 1 |
Descriptor
Error Patterns | 3 |
Evaluation Research | 3 |
Computation | 2 |
Evaluation Methods | 2 |
Monte Carlo Methods | 2 |
Sample Size | 2 |
Correlation | 1 |
Error Correction | 1 |
Factor Analysis | 1 |
Intervals | 1 |
Item Response Theory | 1 |
More ▼ |
Source
Psychological Methods | 3 |
Author
Chan, Daniel W.-L. | 1 |
Chan, Wai | 1 |
Forero, Carlos G. | 1 |
Harwell, Michael R. | 1 |
Maydeu-Olivares, Alberto | 1 |
Serlin, Ronald C. | 1 |
Publication Type
Journal Articles | 3 |
Reports - Research | 2 |
Reports - Evaluative | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Forero, Carlos G.; Maydeu-Olivares, Alberto – Psychological Methods, 2009
The performance of parameter estimates and standard errors in estimating F. Samejima's graded response model was examined across 324 conditions. Full information maximum likelihood (FIML) was compared with a 3-stage estimator for categorical item factor analysis (CIFA) when the unweighted least squares method was used in CIFA's third stage. CIFA…
Descriptors: Factor Analysis, Least Squares Statistics, Computation, Item Response Theory
Chan, Wai; Chan, Daniel W.-L. – Psychological Methods, 2004
The standard Pearson correlation coefficient is a biased estimator of the true population correlation, ?, when the predictor and the criterion are range restricted. To correct the bias, the correlation corrected for range restriction, r-sub(c), has been recommended, and a standard formula based on asymptotic results for estimating its standard…
Descriptors: Computation, Intervals, Sample Size, Monte Carlo Methods
Serlin, Ronald C.; Harwell, Michael R. – Psychological Methods, 2004
It is well-known that for normally distributed errors parametric tests are optimal statistically, but perhaps less well-known is that when normality does not hold, nonparametric tests frequently possess greater statistical power than parametric tests, while controlling Type I error rate. However, the use of nonparametric procedures has been…
Descriptors: Multiple Regression Analysis, Monte Carlo Methods, Nonparametric Statistics, Error Patterns